Sensors are set to be installed across Reading station to capture live, real-time data on the station’s energy usage in a bid to help cut the station’s carbon emissions and improve its energy performance.
This innovative approach to understanding and improving the station’s energy performance is thanks to a specialist computer modelling platform that has developed a 'digital twin' of the station including a simulation of its current energy usage. Using existing, historical data and modelling, a number of opportunities have been identified that are predicted could result in around a 20% improvement on the station’s carbon emissions and energy performance.
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Network Rail has team up with Atkins – a member of the SNC-Lavalin Group – and Cardiff University to develop this ‘digital twin’ of Reading station, utilising Cardiff University’s Computational Urban Sustainability Platform (CUSP).
Using this data and computer modelling to create baselines for the station's energy consumption and carbon emissions, CUSP has been used to map out ways of improving the station’s performance via energy efficiency measures whilst exploring further possible changes and the potential impact this could have on making additional energy savings.
A number of ways to reduce energy expenditure and carbon emissions with minimal costs have been identified, including:
• Improved lighting controls such as dimming when an area of the station is not in use.
• Turning off machinery such as escalators when not in use or overnight when train services aren't in operation.
In addition to the data being collected by the sensors at the station, passenger numbers and research to understand passenger and station-user behaviour will also be recorded to understand how identified energy savings might impact their safety and experiences when in the station.
